DOI: 10.1016/j.foreco.2013.07.040
Scopus记录号: 2-s2.0-84883500189
论文题名: On the evaluation of competition indices - The problem of overlapping samples
作者: Pedersen R.T. ; Næsset E. ; Gobakken T. ; Bollandsås O.M.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2013
卷: 310 起始页码: 120
结束页码: 133
语种: 英语
英文关键词: Airborne laser scanning
; Competition indices
; National forest inventory
; Plot edge bias
; Spatial autocorrelation
Scopus关键词: Airborne Laser scanning
; Competition index
; Edge bias
; National forest inventories
; Spatial autocorrelations
; Autocorrelation
; Laser applications
; Forestry
; airborne sensing
; autocorrelation
; competition (ecology)
; correlation
; error analysis
; forest inventory
; sampling
; spatial variation
; statistical analysis
; Competition
; Forestry
; Inventories
; Lasers
; Scanning
; Australia
; Nora Creek
; Queensland
英文摘要: We discuss statistical concerns regarding evaluation of three types of individual tree competition indices (non-spatially, spatially explicit and based on airborne laser scanning), with special attention to the method of selection of competitors, and the spatial dependency and smoothing caused by overlapping samples of competitors. We quantify the effect of spatial autocorrelation on the effective sample size for various search methods, to reveal potential type I statistical error, for a sample of 557 plots of the Norwegian National Forest Inventory located in the Hedmark Country. Our results show that spatial autocorrelation mostly appears when competitors are selected within short search radii (3-4). m of the subject tree. However, when simultaneously accounting for the impact of spatial autocorrelation on the effective sample size between individual tree growth at breast height and competition, the effect appears to be neglect-able. This result is verified by testing if the change in the effective degrees of freedom in the Spearman rank correlation t-test for the Clifford et al. correction and a spatial bootstrap method, relative to the classical t-test effective degrees of freedom, are correlated with different measures of stand structure. This ratio showed no systematic variation across measures of plot micro and macro-scale variation like Loreyś mean height, the Gini-coefficient of tree basal area or volume per hectare. The conclusion seems indifferent to plot edge bias correction. A linear mixed model with spatial covariance structure confirmed that sample overlap does not cause serious spatial dependence. Moreover, a median based statistical test revealed a significant smoothing effect, with increasing search radii of competitors, which causes loss of variation. However, the smoothing does not decrease the ability of the competition indices to correlate with individual tree growth at breast height within search radii of 12. m, and thus it does not represent any problem for prediction. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/66326
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 1423, Ås, Norway
Recommended Citation:
Pedersen R.T.,Næsset E.,Gobakken T.,et al. On the evaluation of competition indices - The problem of overlapping samples[J]. Forest Ecology and Management,2013-01-01,310